Search results for: graphics processing units
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5131

Search results for: graphics processing units

3361 Supplemental VisCo-friction Damping for Dynamical Structural Systems

Authors: Sharad Singh, Ajay Kumar Sinha

Abstract:

Coupled dampers like viscoelastic-frictional dampers for supplemental damping are a newer technique. In this paper, innovative Visco-frictional damping models have been presented and investigated. This paper attempts to couple frictional and fluid viscous dampers into a single unit of supplemental dampers. Visco-frictional damping model is developed by series and parallel coupling of frictional and fluid viscous dampers using Maxwell and Kelvin-Voigat models. The time analysis has been performed using numerical simulation on an SDOF system with varying fundamental periods, subject to a set of 12 ground motions. The simulation was performed using the direct time integration method. MATLAB programming tool was used to carry out the numerical simulation. The response behavior has been analyzed for the varying time period and added damping. This paper compares the response reduction behavior of the two modes of coupling. This paper highlights the performance efficiency of the suggested damping models. It also presents a mathematical modeling approach to visco-frictional dampers and simultaneously suggests the suitable mode of coupling between the two sub-units.

Keywords: hysteretic damping, Kelvin model, Maxwell model, parallel coupling, series coupling, viscous damping

Procedia PDF Downloads 158
3360 Leveraging Natural Language Processing for Legal Artificial Intelligence: A Longformer Approach for Taiwanese Legal Cases

Authors: Hsin Lee, Hsuan Lee

Abstract:

Legal artificial intelligence (LegalAI) has been increasing applications within legal systems, propelled by advancements in natural language processing (NLP). Compared with general documents, legal case documents are typically long text sequences with intrinsic logical structures. Most existing language models have difficulty understanding the long-distance dependencies between different structures. Another unique challenge is that while the Judiciary of Taiwan has released legal judgments from various levels of courts over the years, there remains a significant obstacle in the lack of labeled datasets. This deficiency makes it difficult to train models with strong generalization capabilities, as well as accurately evaluate model performance. To date, models in Taiwan have yet to be specifically trained on judgment data. Given these challenges, this research proposes a Longformer-based pre-trained language model explicitly devised for retrieving similar judgments in Taiwanese legal documents. This model is trained on a self-constructed dataset, which this research has independently labeled to measure judgment similarities, thereby addressing a void left by the lack of an existing labeled dataset for Taiwanese judgments. This research adopts strategies such as early stopping and gradient clipping to prevent overfitting and manage gradient explosion, respectively, thereby enhancing the model's performance. The model in this research is evaluated using both the dataset and the Average Entropy of Offense-charged Clustering (AEOC) metric, which utilizes the notion of similar case scenarios within the same type of legal cases. Our experimental results illustrate our model's significant advancements in handling similarity comparisons within extensive legal judgments. By enabling more efficient retrieval and analysis of legal case documents, our model holds the potential to facilitate legal research, aid legal decision-making, and contribute to the further development of LegalAI in Taiwan.

Keywords: legal artificial intelligence, computation and language, language model, Taiwanese legal cases

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3359 Effects of Partial Sleep Deprivation on Prefrontal Cognitive Functions in Adolescents

Authors: Nurcihan Kiris

Abstract:

Restricted sleep is common in young adults and adolescents. The results of a few objective studies of sleep deprivation on cognitive performance were not clarified. In particular, the effect of sleep deprivation on the cognitive functions associated with frontal lobe such as attention, executive functions, working memory is not well known. The aim of this study is to investigate the effect of partial sleep deprivation experimentally in adolescents on the cognitive tasks of frontal lobe including working memory, strategic thinking, simple attention, continuous attention, executive functions, and cognitive flexibility. Subjects of the study were recruited from voluntary students of Cukurova University. Eighteen adolescents underwent four consecutive nights of monitored sleep restriction (6–6.5 hr/night) and four nights of sleep extension (10–10.5 hr/night), in counterbalanced order, and separated by a washout period. Following each sleep period, cognitive performance was assessed, at a fixed morning time, using a computerized neuropsychological battery based on frontal lobe functions task, a timed test providing both accuracy and reaction time outcome measures. Only the spatial working memory performance of cognitive tasks was found to be statistically lower in a restricted sleep condition than the extended sleep condition. On the other hand, there was no significant difference in the performance of cognitive tasks evaluating simple attention, constant attention, executive functions, and cognitive flexibility. It is thought that especially the spatial working memory and strategic thinking skills of adolescents may be susceptible to sleep deprivation. On the other hand, adolescents are predicted to be optimally successful in ideal sleep conditions, especially in the circumstances requiring for the short term storage of visual information, processing of stored information, and strategic thinking. The findings of this study may also be associated with possible negative functional effects on the processing of academic social and emotional inputs in adolescents for partial sleep deprivation. Acknowledgment: This research was supported by Cukurova University Scientific Research Projects Unit.

Keywords: attention, cognitive functions, sleep deprivation, working memory

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3358 Fuzzy Total Factor Productivity by Credibility Theory

Authors: Shivi Agarwal, Trilok Mathur

Abstract:

This paper proposes the method to measure the total factor productivity (TFP) change by credibility theory for fuzzy input and output variables. Total factor productivity change has been widely studied with crisp input and output variables, however, in some cases, input and output data of decision-making units (DMUs) can be measured with uncertainty. These data can be represented as linguistic variable characterized by fuzzy numbers. Malmquist productivity index (MPI) is widely used to estimate the TFP change by calculating the total factor productivity of a DMU for different time periods using data envelopment analysis (DEA). The fuzzy DEA (FDEA) model is solved using the credibility theory. The results of FDEA is used to measure the TFP change for fuzzy input and output variables. Finally, numerical examples are presented to illustrate the proposed method to measure the TFP change input and output variables. The suggested methodology can be utilized for performance evaluation of DMUs and help to assess the level of integration. The methodology can also apply to rank the DMUs and can find out the DMUs that are lagging behind and make recommendations as to how they can improve their performance to bring them at par with other DMUs.

Keywords: chance-constrained programming, credibility theory, data envelopment analysis, fuzzy data, Malmquist productivity index

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3357 A Joint Possibilistic-Probabilistic Tool for Load Flow Uncertainty Assessment-Part II: Case Studies

Authors: Morteza Aien, Masoud Rashidinejad, Mahmud Fotuhi-Firuzabad

Abstract:

Power systems are innately uncertain systems. To face with such uncertain systems, robust uncertainty assessment tools are appealed. This paper inspects the uncertainty assessment formulation of the load flow (LF) problem considering different kinds of uncertainties, developed in its companion paper through some case studies. The proposed methodology is based on the evidence theory and joint propagation of possibilistic and probabilistic uncertainties. The load and wind power generation are considered as probabilistic uncertain variables and the electric vehicles (EVs) and gas turbine distributed generation (DG) units are considered as possibilistic uncertain variables. The cumulative distribution function (CDF) of the system output parameters obtained by the pure probabilistic method lies within the belief and plausibility functions obtained by the joint propagation approach. Furthermore, the imprecision in the DG parameters is explicitly reflected by the gap between the belief and plausibility functions. This gap, due to the epistemic uncertainty on the DG resources parameters grows as the penetration level increases.

Keywords: electric vehicles, joint possibilistic- probabilistic uncertainty modeling, uncertain load flow, wind turbine generator

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3356 Yacht DB Construction Based on Five Essentials of Sailing

Authors: Jae-Neung Lee, Myung-Won Lee, Jung-Su Han, Keun-Chang Kwak

Abstract:

The paper established DB on the basis of five sailing essentials in the real yachting environment. It obtained the yacht condition (tilt, speed and course), surrounding circumstances (wind direction and speed) and user motion. Gopro camera for image processing was used to recognize the user motion and tilt sensor was employed to see the yacht balance. In addition, GPS for course, wind speed and direction sensor and marked suit were employed.

Keywords: DB consturuction, yacht, five essentials of sailing, marker, Gps

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3355 Sorption of Charged Organic Dyes from Anionic Hydrogels

Authors: Georgios Linardatos, Miltiadis Zamparas, Vlasoula Bekiari, Georgios Bokias, Georgios Hotos

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Hydrogels are three-dimensional, hydrophilic, polymeric networks composed of homopolymers or copolymers and are insoluble in water due to the presence of chemical or physical cross-links. When hydrogels come in contact with aqueous solutions, they can effectively sorb and retain the dissolved substances, depending on the nature of the monomeric units comprising the hydrogel. For this reason, hydrogels have been proposed in several studies as water purification agents. At the present work anionic hydrogels bearing negatively charged –COO- groups were prepared and investigated. These gels are based on sodium acrylate (ANa), either homopolymerized (poly(sodiumacrylate), PANa) or copolymerized (P(DMAM-co-ANa)) with N,N Dimethylacrylamide (DMAM). The hydrogels were used to extract some model organic dyes from water. It is found that cationic dyes are strongly sorbed and retained by the hydrogels, while sorption of anionic dyes was negligible. In all cases it was found that both maximum sorption capacity and equilibrium binding constant varied from one dye to the other depending on the chemical structure of the dye, the presence of functional chemical groups and the hydrophobic-hydrophilic balance. Finally, the nonionic hydrogel of the homopolymer poly(N,N-dimethylacrylamide), PDMAM, was also used for reasons of comparison.

Keywords: anionic organic hydrogels, sorption, organic dyes, water purification agents

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3354 The Hypoglycemic Grab Back (HOGG): Preparing Hypo-Screen-Bags to Streamline the Time-Consuming Process of Administering Glucose Systemic Correction

Authors: Mai Ali

Abstract:

Background: Preparing Hypo-screen-bags in advance streamlines the time-consuming process of administering glucose systemic correction. Additionally, Hypo-Screen Grab Bags are widely adopted in UK hospitals. Aim: The aim of the study is to improve hypoglycemia screening efficiency and equipment accessibility by streamlining item access to grab bag restocking staff. Methodology: The study centered on neonatal wards at LGI & St. James Neonatal Unit and related units. A web-based survey was conducted to evaluate local practices, gathering 21 responses from relevant general staff. The survey outcomes: (1) The demand for accessible grab bags is evident for smoother processes. (2) The potential to enhance efficiency through improved preparation of hypo-screen grab bags. Intervention: A Hypo-Screen Grab Bag was designed, including checklists for stocked items and required samples. Medical staff oversee restocking after use. Conclusion: The study successfully improved hypoglycemia screening efficiency and aided junior staff with accessible supplies and a user-friendly checklist.

Keywords: neonatal hypoglycemia, grab bag, hypo-screening, junior staff

Procedia PDF Downloads 63
3353 Multimodal Integration of EEG, fMRI and Positron Emission Tomography Data Using Principal Component Analysis for Prognosis in Coma Patients

Authors: Denis Jordan, Daniel Golkowski, Mathias Lukas, Katharina Merz, Caroline Mlynarcik, Max Maurer, Valentin Riedl, Stefan Foerster, Eberhard F. Kochs, Andreas Bender, Ruediger Ilg

Abstract:

Introduction: So far, clinical assessments that rely on behavioral responses to differentiate coma states or even predict outcome in coma patients are unreliable, e.g. because of some patients’ motor disabilities. The present study was aimed to provide prognosis in coma patients using markers from electroencephalogram (EEG), blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). Unsuperwised principal component analysis (PCA) was used for multimodal integration of markers. Methods: Approved by the local ethics committee of the Technical University of Munich (Germany) 20 patients (aged 18-89) with severe brain damage were acquired through intensive care units at the Klinikum rechts der Isar in Munich and at the Therapiezentrum Burgau (Germany). At the day of EEG/fMRI/PET measurement (date I) patients (<3.5 month in coma) were grouped in the minimal conscious state (MCS) or vegetative state (VS) on the basis of their clinical presentation (coma recovery scale-revised, CRS-R). Follow-up assessment (date II) was also based on CRS-R in a period of 8 to 24 month after date I. At date I, 63 channel EEG (Brain Products, Gilching, Germany) was recorded outside the scanner, and subsequently simultaneous FDG-PET/fMRI was acquired on an integrated Siemens Biograph mMR 3T scanner (Siemens Healthineers, Erlangen Germany). Power spectral densities, permutation entropy (PE) and symbolic transfer entropy (STE) were calculated in/between frontal, temporal, parietal and occipital EEG channels. PE and STE are based on symbolic time series analysis and were already introduced as robust markers separating wakefulness from unconsciousness in EEG during general anesthesia. While PE quantifies the regularity structure of the neighboring order of signal values (a surrogate of cortical information processing), STE reflects information transfer between two signals (a surrogate of directed connectivity in cortical networks). fMRI was carried out using SPM12 (Wellcome Trust Center for Neuroimaging, University of London, UK). Functional images were realigned, segmented, normalized and smoothed. PET was acquired for 45 minutes in list-mode. For absolute quantification of brain’s glucose consumption rate in FDG-PET, kinetic modelling was performed with Patlak’s plot method. BOLD signal intensity in fMRI and glucose uptake in PET was calculated in 8 distinct cortical areas. PCA was performed over all markers from EEG/fMRI/PET. Prognosis (persistent VS and deceased patients vs. recovery to MCS/awake from date I to date II) was evaluated using the area under the curve (AUC) including bootstrap confidence intervals (CI, *: p<0.05). Results: Prognosis was reliably indicated by the first component of PCA (AUC=0.99*, CI=0.92-1.00) showing a higher AUC when compared to the best single markers (EEG: AUC<0.96*, fMRI: AUC<0.86*, PET: AUC<0.60). CRS-R did not show prediction (AUC=0.51, CI=0.29-0.78). Conclusion: In a multimodal analysis of EEG/fMRI/PET in coma patients, PCA lead to a reliable prognosis. The impact of this result is evident, as clinical estimates of prognosis are inapt at time and could be supported by quantitative biomarkers from EEG, fMRI and PET. Due to the small sample size, further investigations are required, in particular allowing superwised learning instead of the basic approach of unsuperwised PCA.

Keywords: coma states and prognosis, electroencephalogram, entropy, functional magnetic resonance imaging, machine learning, positron emission tomography, principal component analysis

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3352 Vascular Targeted Photodynamic Therapy Monitored by Real-Time Laser Speckle Imaging

Authors: Ruth Goldschmidt, Vyacheslav Kalchenko, Lilah Agemy, Rachel Elmoalem, Avigdor Scherz

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Vascular Targeted Photodynamic therapy (VTP) is a new modality for selective cancer treatment that leads to the complete tumor ablation. A photosensitizer, a bacteriochlorophyll derivative in our case, is first administered to the patient and followed by the illumination of the tumor area, by a near-IR laser for its photoactivation. The photoactivated drug releases reactive oxygen species (ROS) in the circulation, which reacts with blood cells and the endothelium leading to the occlusion of the blood vasculature. If the blood vessels are only partially closed, the tumor may recover, and cancer cells could survive. On the other hand, excessive treatment may lead to toxicity of healthy tissues nearby. Simultaneous VTP monitoring and image processing independent of the photoexcitation laser has not yet been reported, to our knowledge. Here we present a method for blood flow monitoring, using a real-time laser speckle imaging (RTLSI) in the tumor during VTP. We have synthesized over the years a library of bacteriochlorophyll derivatives, among them WST11 and STL-6014. Both are water soluble derivatives that are retained in the blood vasculature through their partial binding to HSA. WST11 has been approved in Mexico for VTP treatment of prostate cancer at a certain drug dose, and time/intensity of illumination. Application to other bacteriochlorophyll derivatives or other cancers may require different treatment parameters (such as light/drug administration). VTP parameters for STL-6014 are still under study. This new derivative mainly differs from WST11 by its lack of the central Palladium, and its conjugation to an Arg-Gly-Asp (RGD) sequence. RGD is a tumor-specific ligand that is used for targeting the necrotic tumor domains through its affinity to αVβ3 integrin receptors. This enables the study of cell-targeted VTP. We developed a special RTLSI module, based on Labview software environment for data processing. The new module enables to acquire raw laser speckle images and calculate the values of the laser temporal statistics of time-integrated speckles in real time, without additional off-line processing. Using RTLSI, we could monitor the tumor’s blood flow following VTP in a CT26 colon carcinoma ear model. VTP with WST11 induced an immediate slow down of the blood flow within the tumor and a complete final flow arrest, after some sporadic reperfusions. If the irradiation continued further, the blood flow stopped also in the blood vessels of the surrounding healthy tissue. This emphasizes the significance of light dose control. Using our RTLSI system, we could prevent any additional healthy tissue damage by controlling the illumination time and restrict blood flow arrest within the tumor only. In addition, we found that VTP with STL-6014 was the most effective when the photoactivation was conducted 4h post-injection, in terms of tumor ablation success in-vivo and blood vessel flow arrest. In conclusion, RTSLI application should allow to optimize VTP efficacy vs. toxicity in both the preclinical and clinical arenas.

Keywords: blood vessel occlusion, cancer treatment, photodynamic therapy, real time imaging

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3351 Economics and Management Information Systems: Institute of Management and Technology Enugu a Case Study

Authors: Cletus Agbowo

Abstract:

Standard principles, rules, regulations, norms and guides are necessities in practice especially in the Economics and management information system Institute of management of and technology (IMT) Enugu a case sturdy as presented by the presenter. Without mincing words, the fundamental bottle neck of management is economics, how to select to engage merger productivity resources to achieve uncountable objectives without tears. Management information system inevitably become bound up in organizational politics because the influence access to a key resource – namely information. Economics and management information can effect who does what to whom, when, where and how in an organization. In great institutions like the Institute of Management and Technology (IMT) Enugu a case study many new information systems require changes in personnel, individual routines that can be painful for those involved and require retraining and additional effort may or may not be compensated. In a nut shell, because management information system potentially change an organization’s structure, culture, business processes, and strategy, there is often considerable resistance to them when they are introduced. The case study have many schools, departments, divisions and units which needs research on economics and management information systems. A system can be defined as a set of interrelated components and / or elements, which reacts with input to produce output. A department in an organization is a system. The researcher is faced to itemize the practical challenges encountered and solution adopted by the Institute Management and Enugu state government.

Keywords: economics, information, management, productivity, regulations

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3350 RSU Aggregated Message Delivery for VANET

Authors: Auxeeliya Jesudoss, Ashraph Sulaiman, Ratnakar Kotnana

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V2V communication brings up several questions of scalability issues although message sharing in vehicular ad-hoc networks comprises of both Vehicle-to-Vehicle communications (V2V) and Vehicle to Infrastructure communication (V2I). It is not an easy task for a vehicle to verify all signatures of the messages sent by its neighboring vehicles in a timely manner, without resulting in message loss. Moreover, the communication overhead of a vehicle to authenticate another vehicle would increase together with the security of the system. Another issue to be addressed is the continuous mobility of vehicles which requires at least some information on the node’s own position to be revealed to the neighboring vehicles. This may facilitate the attacker to congregate information on a node’s position or its mobility patterns. In order to tackle these issues, this paper introduces a RSU aggregated message deliverance scheme called RAMeD. With RAMeD, roadside units (RSUs) are responsible for verifying the identity of the vehicles entering in its range, collect messages from genuine vehicles and to aggregate similar messages into groups before sending them to all the vehicles in its communication range. This aggregation will tremendously improve the rate of message delivery and reduce the message lose ratio by avoiding similar messages being sent to the vehicles redundantly. The proposed protocol is analyzed extensively to evaluate its merits and efficiency for vehicular communication.

Keywords: vehicular ad-hoc networks, V2V, V2I, VANET communication, scalability, message aggregation

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3349 Investigating the Editing's Effect of Advertising Photos on the Virtual Purchase Decision Based on the Quantitative Electroencephalogram (EEG) Parameters

Authors: Parya Tabei, Maryam Habibifar

Abstract:

Decision-making is an important cognitive function that can be defined as the process of choosing an option among available options to achieve a specific goal. Consumer ‘need’ is the main reason for purchasing decisions. Human decision-making while buying products online is subject to various factors, one of which is the quality and effect of advertising photos. Advertising photo editing can have a significant impact on people's virtual purchase decisions. This technique helps improve the quality and overall appearance of photos by adjusting various aspects such as brightness, contrast, colors, cropping, resizing, and adding filters. This study, by examining the effect of editing advertising photos on the virtual purchase decision using EEG data, tries to investigate the effect of edited images on the decision-making of customers. A group of 30 participants were asked to react to 24 edited and unedited images while their EEG was recorded. Analysis of the EEG data revealed increased alpha wave activity in the occipital regions (O1, O2) for both edited and unedited images, which is related to visual processing and attention. Additionally, there was an increase in beta wave activity in the frontal regions (FP1, FP2, F4, F8) when participants viewed edited images, suggesting involvement in cognitive processes such as decision-making and evaluating advertising content. Gamma wave activity also increased in various regions, especially the frontal and parietal regions, which are associated with higher cognitive functions, such as attention, memory, and perception, when viewing the edited images. While the visual processing reflected by alpha waves remained consistent across different visual conditions, editing advertising photos appeared to boost neural activity in frontal and parietal regions associated with decision-making processes. These Findings suggest that photo editing could potentially influence consumer perceptions during virtual shopping experiences by modulating brain activity related to product assessment and purchase decisions.

Keywords: virtual purchase decision, advertising photo, EEG parameters, decision Making

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3348 Mg AZ31B Alloy Processed through ECASD

Authors: P. Fernández-Morales, D. Peláez, C. Isaza, J. M. Meza, E. Mendoza

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Mg AZ31B alloy sheets were processed through equal-channel angular sheet drawing (ECASD) process, following the route A and C at room temperature and varying the processing speed. SEM was used to analyze the microstructure. The grain size was refined and presence of twins was observed. Vickers microhardness and tensile testing were carried out to evaluate the mechanical properties, showing in general; a remarkable increase in the first pass and slight increases during subsequent passes and, that the route C produces better uniform properties distribution through the thickness of the samples.

Keywords: ECASD, Mg Alloy, mechanical properties, microstructure

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3347 Mechanical Properties of Poly(Propylene)-Based Graphene Nanocomposites

Authors: Luiza Melo De Lima, Tito Trindade, Jose M. Oliveira

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The development of thermoplastic-based graphene nanocomposites has been of great interest not only to the scientific community but also to different industrial sectors. Due to the possible improvement of performance and weight reduction, thermoplastic nanocomposites are a great promise as a new class of materials. These nanocomposites are of relevance for the automotive industry, namely because the emission limits of CO2 emissions imposed by the European Commission (EC) regulations can be fulfilled without compromising the car’s performance but by reducing its weight. Thermoplastic polymers have some advantages over thermosetting polymers such as higher productivity, lower density, and recyclability. In the automotive industry, for example, poly(propylene) (PP) is a common thermoplastic polymer, which represents more than half of the polymeric raw material used in automotive parts. Graphene-based materials (GBM) are potential nanofillers that can improve the properties of polymer matrices at very low loading. In comparison to other composites, such as fiber-based composites, weight reduction can positively affect their processing and future applications. However, the properties and performance of GBM/polymer nanocomposites depend on the type of GBM and polymer matrix, the degree of dispersion, and especially the type of interactions between the fillers and the polymer matrix. In order to take advantage of the superior mechanical strength of GBM, strong interfacial strength between GBM and the polymer matrix is required for efficient stress transfer from GBM to the polymer. Thus, chemical compatibilizers and physicochemical modifications have been reported as important tools during the processing of these nanocomposites. In this study, PP-based nanocomposites were obtained by a simple melt blending technique, using a Brabender type mixer machine. Graphene nanoplatelets (GnPs) were applied as structural reinforcement. Two compatibilizers were used to improve the interaction between PP matrix and GnPs: PP graft maleic anhydride (PPgMA) and PPgMA modified with tertiary amine alcohol (PPgDM). The samples for tensile and Charpy impact tests were obtained by injection molding. The results suggested the GnPs presence can increase the mechanical strength of the polymer. However, it was verified that the GnPs presence can promote a decrease of impact resistance, turning the nanocomposites more fragile than neat PP. The compatibilizers’ incorporation increases the impact resistance, suggesting that the compatibilizers can enhance the adhesion between PP and GnPs. Compared to neat PP, Young’s modulus of non-compatibilized nanocomposite increase demonstrated that GnPs incorporation can promote a stiffness improvement of the polymer. This trend can be related to the several physical crosslinking points between the PP matrix and the GnPs. Furthermore, the decrease of strain at a yield of PP/GnPs, together with the enhancement of Young’s modulus, confirms that the GnPs incorporation led to an increase in stiffness but to a decrease in toughness. Moreover, the results demonstrated that incorporation of compatibilizers did not affect Young’s modulus and strain at yield results compared to non-compatibilized nanocomposite. The incorporation of these compatibilizers showed an improvement of nanocomposites’ mechanical properties compared both to those the non-compatibilized nanocomposite and to a PP sample used as reference.

Keywords: graphene nanoplatelets, mechanical properties, melt blending processing, poly(propylene)-based nanocomposites

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3346 Enhancing Students’ Academic Engagement in Mathematics through a “Concept+Language Mapping” Approach

Authors: Jodie Lee, Lorena Chan, Esther Tong

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Hong Kong students face a unique learning environment. Starting from the 2010/2011 school year, The Education Bureau (EDB) of the Government of the Hong Kong Special Administrative Region implemented the fine-tuned Medium of Instruction (MOI) arrangements for secondary schools. Since then, secondary schools in Hong Kong have been given the flexibility to decide the most appropriate MOI arrangements for their schools and under the new academic structure for senior secondary education, particularly on the compulsory part of the mathematics curriculum. In 2019, Hong Kong Diploma of Secondary Education Examination (HKDSE), over 40% of school day candidates attempted the Mathematics Compulsory Part examination in the Chinese version while the rest took the English version. Moreover, only 14.38% of candidates sat for one of the extended Mathematics modules. This results in a serious of intricate issues to students’ learning in post-secondary education programmes. It is worth to note that when students further pursue to an higher education in Hong Kong or even oversea, they may facing substantial difficulties in transiting learning from learning mathematics in their mother tongue in Chinese-medium instruction (CMI) secondary schools to an English-medium learning environment. Some students understood the mathematics concepts were found to fail to fulfill the course requirements at college or university due to their learning experience in secondary study at CMI. They are particularly weak in comprehending the mathematics questions when they are doing their assessment or attempting the test/examination. A government funded project was conducted with the aims of providing integrated learning context and language support to students with a lower level of numeracy and/or with CMI learning experience. By introducing this “integrated concept + language mapping approach”, students can cope with the learning challenges in the compulsory English-medium mathematics and statistics subjects in their tertiary education. Ultimately, in the hope that students can enhance their mathematical ability, analytical skills, and numerical sense for their lifelong learning. The “Concept + Language Mapping “(CLM) approach was adopted and tried out in the bridging courses for students with a lower level of numeracy and/or with CMI learning experiences. At the beginning of each class, a pre-test was conducted, and class time was then devoted to introducing the concepts by CLM approach. For each concept, the key thematic items and their different semantic relations are presented using graphics and animations via the CLM approach. At the end of each class, a post-test was conducted. Quantitative data analysis was performed to study the effect on students’ learning via the CLM approach. Stakeholders' feedbacks were collected to estimate the effectiveness of the CLM approach in facilitating both content and language learning. The results based on both students’ and lecturers’ feedback indicated positive outcomes on adopting the CLM approach to enhance the mathematical ability and analytical skills of CMI students.

Keywords: mathematics, Concept+Language Mapping, level of numeracy, medium of instruction

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3345 A Novel Machine Learning Approach to Aid Agrammatism in Non-fluent Aphasia

Authors: Rohan Bhasin

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Agrammatism in non-fluent Aphasia Cases can be defined as a language disorder wherein a patient can only use content words ( nouns, verbs and adjectives ) for communication and their speech is devoid of functional word types like conjunctions and articles, generating speech of with extremely rudimentary grammar . Past approaches involve Speech Therapy of some order with conversation analysis used to analyse pre-therapy speech patterns and qualitative changes in conversational behaviour after therapy. We describe this approach as a novel method to generate functional words (prepositions, articles, ) around content words ( nouns, verbs and adjectives ) using a combination of Natural Language Processing and Deep Learning algorithms. The applications of this approach can be used to assist communication. The approach the paper investigates is : LSTMs or Seq2Seq: A sequence2sequence approach (seq2seq) or LSTM would take in a sequence of inputs and output sequence. This approach needs a significant amount of training data, with each training data containing pairs such as (content words, complete sentence). We generate such data by starting with complete sentences from a text source, removing functional words to get just the content words. However, this approach would require a lot of training data to get a coherent input. The assumptions of this approach is that the content words received in the inputs of both text models are to be preserved, i.e, won't alter after the functional grammar is slotted in. This is a potential limit to cases of severe Agrammatism where such order might not be inherently correct. The applications of this approach can be used to assist communication mild Agrammatism in non-fluent Aphasia Cases. Thus by generating these function words around the content words, we can provide meaningful sentence options to the patient for articulate conversations. Thus our project translates the use case of generating sentences from content-specific words into an assistive technology for non-Fluent Aphasia Patients.

Keywords: aphasia, expressive aphasia, assistive algorithms, neurology, machine learning, natural language processing, language disorder, behaviour disorder, sequence to sequence, LSTM

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3344 Variable Selection in a Data Envelopment Analysis Model by Multiple Proportions Comparison

Authors: Jirawan Jitthavech, Vichit Lorchirachoonkul

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A statistical procedure using multiple comparisons test for proportions is proposed for variable selection in a data envelopment analysis (DEA) model. The test statistic in the multiple comparisons is the proportion of efficient decision making units (DMUs) in a DEA model. Three methods of multiple comparisons test for proportions: multiple Z tests with Bonferroni correction, multiple tests in 2Xc crosstabulation and the Marascuilo procedure, are used in the proposed statistical procedure of iteratively eliminating the variables in a backward manner. Two simulation populations of moderately and lowly correlated variables are used to compare the results of the statistical procedure using three methods of multiple comparisons test for proportions with the hypothesis testing of the efficiency contribution measure. From the simulation results, it can be concluded that the proposed statistical procedure using multiple Z tests for proportions with Bonferroni correction clearly outperforms the proposed statistical procedure using the remaining two methods of multiple comparisons and the hypothesis testing of the efficiency contribution measure.

Keywords: Bonferroni correction, efficient DMUs, Marascuilo procedure, Pastor et al. method, 2xc crosstabulation

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3343 Detection of Phoneme [S] Mispronounciation for Sigmatism Diagnosis in Adults

Authors: Michal Krecichwost, Zauzanna Miodonska, Pawel Badura

Abstract:

The diagnosis of sigmatism is mostly based on the observation of articulatory organs. It is, however, not always possible to precisely observe the vocal apparatus, in particular in the oral cavity of the patient. Speech processing can allow to objectify the therapy and simplify the verification of its progress. In the described study the methodology for classification of incorrectly pronounced phoneme [s] is proposed. The recordings come from adults. They were registered with the speech recorder at the sampling rate of 44.1 kHz and the resolution of 16 bit. The database of pathological and normative speech has been collected for the study including reference assessments provided by the speech therapy experts. Ten adult subjects were asked to simulate a certain type of stigmatism under the speech therapy expert supervision. In the recordings, the analyzed phone [s] was surrounded by vowels, viz: ASA, ESE, ISI, SPA, USU, YSY. Thirteen MFCC (mel-frequency cepstral coefficients) and RMS (root mean square) values are calculated within each frame being a part of the analyzed phoneme. Additionally, 3 fricative formants along with corresponding amplitudes are determined for the entire segment. In order to aggregate the information within the segment, the average value of each MFCC coefficient is calculated. All features of other types are aggregated by means of their 75th percentile. The proposed method of features aggregation reduces the size of the feature vector used in the classification. Binary SVM (support vector machine) classifier is employed at the phoneme recognition stage. The first group consists of pathological phones, while the other of the normative ones. The proposed feature vector yields classification sensitivity and specificity measures above 90% level in case of individual logo phones. The employment of a fricative formants-based information improves the sole-MFCC classification results average of 5 percentage points. The study shows that the employment of specific parameters for the selected phones improves the efficiency of pathology detection referred to the traditional methods of speech signal parameterization.

Keywords: computer-aided pronunciation evaluation, sibilants, sigmatism diagnosis, speech processing

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3342 Determination of Chemical Contaminants in UHT Milk Consumed in Sharjah, UAE

Authors: Adem Rama, Rabiha Seboussi, Mahmoud Muhamadin, Sultan Alzarooni, Fatima Mohamed, Khuloud Al Ali

Abstract:

To assess public health hazards associated with the occurrence of Antibiotics and AFM1 residues in UHT milk, a survey was carried out in Sharjah, UAE. In the present study, a total of 42 UHT milk samples analyzed were from different commercial brands manufactured in industrial dairy units in the UAE and from foreign producers. Milk samples were collected for four months (January to April 2020). The occurrence and concentration range of Antibiotics (Streptomycin and Gentamycin) and AFM1 in the samples were investigated by applying the ELISA method. According to the methodology used in this study, in total, 2 (5%) out of 42(95%) samples tested positive on the presence of AFM1. While, 1(2.4%) out of 41(97.6%) positive samples were found to contain Streptomycin and Gentamycin, respectively. The positive incidence of AFM1 in the UHT milk samples ranged from 58.8 to 1074 µg/L, for Streptomycin from up to 1004 µg/L, and Gentamycin up to 6909 µg/L. There were no positive samples found in locally produced UHT milk. AFM1 and antibiotic levels in positive samples UHT milk samples exceeded the maximum tolerable limits as set by the European Union - EC guidelines/standards. These levels in the samples show a presence of contaminants that might constitute a human health risk in Sharjah. The results of this study imply that more emphasis should be given to the routine inspection of milk and dairy products in the Sharjah region.

Keywords: milk, contaminant residues, ELISA, public health, Sharjah

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3341 Design and 3D-Printout of The Stack-Corrugate-Sheel Core Sandwiched Decks for The Bridging System

Authors: K. Kamal

Abstract:

Structural sandwich panels with core of Advanced Composites Laminates l Honeycombs / PU-foams are used in aerospace applications and are also fabricated for use now in some civil engineering applications. An all Advanced Composites Foot Over Bridge (FOB) system, designed and developed for pedestrian traffic is one such application earlier, may be cited as an example here. During development stage of this FoB, a profile of its decks was then spurred as a single corrugate sheet core sandwiched between two Glass Fibre Reinforced Plastics(GFRP) flat laminates. Once successfully fabricated and used, these decks did prove suitable also to form other structure on assembly, such as, erecting temporary shelters. Such corrugated sheet core profile sandwiched panels were then also tried using the construction materials but any conventional method of construction only posed certain difficulties in achieving the required core profile monolithically within the sandwiched slabs and hence it was then abended. Such monolithic construction was, however, subsequently eased out on demonstration by dispensing building materials mix through a suitably designed multi-dispenser system attached to a 3D Printer. This study conducted at lab level was thus reported earlier and it did include the fabrication of a 3D printer in-house first as ‘3DcMP’ as well as on its functional operation, some required sandwich core profiles also been 3D-printed out producing panels hardware. Once a number of these sandwich panels in single corrugated sheet core monolithically printed out, panels were subjected to load test in an experimental set up as also their structural behavior was studied analytically, and subsequently, these results were correlated as reported in the literature. In achieving the required more depths and also to exhibit further the stronger and creating sandwiched decks of better structural and mechanical behavior, further more complex core configuration such as stack corrugate sheets core with a flat mid plane was felt to be the better sandwiched core. Such profile remained as an outcome that turns out merely on stacking of two separately printed out monolithic units of single corrugated sheet core developed earlier as above and bonded them together initially, maintaining a different orientation. For any required sequential understanding of the structural behavior of any such complex profile core sandwiched decks with special emphasis to study of the effect in the variation of corrugation orientation in each distinct tire in this core, it obviously calls for an analytical study first. The rectangular,simply supported decks have therefore been considered for analysis adopting the ‘Advanced Composite Technology(ACT), some numerical results along with some fruitful findings were obtained and these are all presented here in this paper. From this numerical result, it has been observed that a mid flat layer which eventually get created monolethically itself, in addition to eliminating the bonding process in development, has been found to offer more effective bending resistance by such decks subjected to UDL over them. This is understood to have resulted here since the existence of a required shear resistance layer at the mid of the core in this profile, unlike other bending elements. As an addendum to all such efforts made as covered above and was published earlier, this unique stack corrugate sheet core profile sandwiched structural decks, monolithically construction with ease at the site itself, has been printed out from a 3D Printer. On employing 3DcMP and using some innovative building construction materials, holds the future promises of such research & development works since all those several aspects of a 3D printing in construction are now included such as reduction in the required construction time, offering cost effective solutions with freedom in design of any such complex shapes thus can widely now be realized by the modern construction industry.

Keywords: advance composite technology(ACT), corrugated laminates, 3DcMP, foot over bridge (FOB), sandwiched deck units

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3340 From Industry 4.0 to Agriculture 4.0: A Framework to Manage Product Data in Agri-Food Supply Chain for Voluntary Traceability

Authors: Angelo Corallo, Maria Elena Latino, Marta Menegoli

Abstract:

Agri-food value chain involves various stakeholders with different roles. All of them abide by national and international rules and leverage marketing strategies to advance their products. Food products and related processing phases carry with it a big mole of data that are often not used to inform final customer. Some data, if fittingly identified and used, can enhance the single company, and/or the all supply chain creates a math between marketing techniques and voluntary traceability strategies. Moreover, as of late, the world has seen buying-models’ modification: customer is careful on wellbeing and food quality. Food citizenship and food democracy was born, leveraging on transparency, sustainability and food information needs. Internet of Things (IoT) and Analytics, some of the innovative technologies of Industry 4.0, have a significant impact on market and will act as a main thrust towards a genuine ‘4.0 change’ for agriculture. But, realizing a traceability system is not simple because of the complexity of agri-food supply chain, a lot of actors involved, different business models, environmental variations impacting products and/or processes, and extraordinary climate changes. In order to give support to the company involved in a traceability path, starting from business model analysis and related business process a Framework to Manage Product Data in Agri-Food Supply Chain for Voluntary Traceability was conceived. Studying each process task and leveraging on modeling techniques lead to individuate information held by different actors during agri-food supply chain. IoT technologies for data collection and Analytics techniques for data processing supply information useful to increase the efficiency intra-company and competitiveness in the market. The whole information recovered can be shown through IT solutions and mobile application to made accessible to the company, the entire supply chain and the consumer with the view to guaranteeing transparency and quality.

Keywords: agriculture 4.0, agri-food suppy chain, industry 4.0, voluntary traceability

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3339 The Mineralogy of Shales from the Pilbara and How Chemical Weathering Affects the Intact Strength

Authors: Arturo Maldonado

Abstract:

In the iron ore mining industry, the intact strength of rock units is defined using the uniaxial compressive strength (UCS). This parameter is very important for the classification of shale materials, allowing the split between rock and cohesive soils based on the magnitude of UCS. For this research, it is assumed that UCS less than or equal to 1 MPa is representative of soils. Several researchers have anticipated that the magnitude of UCS reduces with weathering progression, also since UCS is a directional property, its magnitude depends upon the rock fabric orientation. Thus, the paper presents how the UCS of shales is affected by both weathering grade and bedding orientation. The mineralogy of shales has been defined using Hyper-spectral and chemical assays to define the mineral constituents of shale and other non-shale materials. Geological classification tools have been used to define distinct lithological types, and in this manner, the author uses mineralogical datasets to recognize and isolate shales from other rock types and develop tertiary plots for fresh and weathered shales. The mineralogical classification of shales has reduced the contamination of lithology types and facilitated the study of the physical factors affecting the intact strength of shales, like anisotropic strength due to bedding orientation. The analysis of mineralogical characteristics of shales is perhaps the most important contribution of this paper to other researchers who may wish to explore similar methods.

Keywords: rock mechanics, mineralogy, shales, weathering, anisotropy

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3338 Casting Lots for Candidature in General Elections: An Un-Named Political System

Authors: Talib Jan Abasindhi

Abstract:

Democracy has reached almost every nuke & corner of the globe. It is well embedded in the political systems found in the majority of the countries in the world. Political parties, their manifestos, and programs are educating their people for better democracy and good governance, as well as service delivery in many countries around the globe. Although democracy in Pakistan by itself is in its infancy stage, yet, there is a region consisting of three districts (administrative units) lying in the North of the country where democracy is yet unknown to a wide range of population bounded into a series of mountains from Himalayan and Karakuram ranges. Political parties are struggling now to get their roots in the area while disrupting the traditional and tribal electoral system prevailing in the region. This paper will shed light on an interesting subject of casting lots for nomination as candidatures for general and local bodies’ elections in Kohistani region in Pakistan. The people of wisdom and knowledge in the modern world deem such societies as uncivilized where these practices are found. No one can believe it in today’s world, yet, this practice has been common in Kohistani region over the past many decades, and there have been many reasons for this too. Through this paper, we shall not only make others aware of the process and procedure practiced in casting the lots in elections in democratic Pakistan, but rather we shall also talk about its very basic reasons and suggestions as a solution for this menace to be eliminated.

Keywords: democracy, casting lots, governance, Kohistani region

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3337 Technical and Practical Aspects of Sizing a Autonomous PV System

Authors: Abdelhak Bouchakour, Mustafa Brahami, Layachi Zaghba

Abstract:

The use of photovoltaic energy offers an inexhaustible supply of energy but also a clean and non-polluting energy, which is a definite advantage. The geographical location of Algeria promotes the development of the use of this energy. Indeed, given the importance of the intensity of the radiation received and the duration of sunshine. For this reason, the objective of our work is to develop a data-processing tool (software) of calculation and optimization of dimensioning of the photovoltaic installations. Our approach of optimization is basing on mathematical models, which amongst other things describe the operation of each part of the installation, the energy production, the storage and the consumption of energy.

Keywords: solar panel, solar radiation, inverter, optimization

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3336 Creating Energy Sustainability in an Enterprise

Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

Abstract:

As we enter the new era of Artificial Intelligence (AI) and Cloud Computing, we mostly rely on the Machine and Natural Language Processing capabilities of AI, and Energy Efficient Hardware and Software Devices in almost every industry sector. In these industry sectors, much emphasis is on developing new and innovative methods for producing and conserving energy and sustaining the depletion of natural resources. The core pillars of sustainability are economic, environmental, and social, which is also informally referred to as the 3 P's (People, Planet and Profits). The 3 P's play a vital role in creating a core Sustainability Model in the Enterprise. Natural resources are continually being depleted, so there is more focus and growing demand for renewable energy. With this growing demand, there is also a growing concern in many industries on how to reduce carbon emissions and conserve natural resources while adopting sustainability in corporate business models and policies. In our paper, we would like to discuss the driving forces such as Climate changes, Natural Disasters, Pandemic, Disruptive Technologies, Corporate Policies, Scaled Business Models and Emerging social media and AI platforms that influence the 3 main pillars of Sustainability (3P’s). Through this paper, we would like to bring an overall perspective on enterprise strategies and the primary focus on bringing cultural shifts in adapting energy-efficient operational models. Overall, many industries across the globe are incorporating core sustainability principles such as reducing energy costs, reducing greenhouse gas (GHG) emissions, reducing waste and increasing recycling, adopting advanced monitoring and metering infrastructure, reducing server footprint and compute resources (Shared IT services, Cloud computing, and Application Modernization) with the vision for a sustainable environment.

Keywords: climate change, pandemic, disruptive technology, government policies, business model, machine learning and natural language processing, AI, social media platform, cloud computing, advanced monitoring, metering infrastructure

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3335 Bystanders' Behavior during Emergencies

Authors: Alan (Avi) Kirschenbaum, Carmit Rapaport

Abstract:

The behavior of bystanders in emergencies and disasters have been examined for over 50 years. Such acts have been cited as contributing to saving lives in terms of providing first responder help until official emergency units can arrive. Several reasons have been suggested for this type of behavior but most focused on a broad segment of individual psychological decision-making processes. Recent theoretical evidence suggests that the external factors for such bystander decisions, mainly disaster community based social contexts factors, are also important. We aim to test these competing arguments. Specifically, we examine alternative explanatory perspectives by focusing on self-efficacy as a proxy for the accepted individual psychological case and contrast it with potential bystander characteristics of the individual as well factors as embedded in the social context of the disaster community. To do so, we will utilize a random sampling of the population from a field study of an urban community in Israel that experienced five years of continuous terror attacks. The results strongly suggest that self-efficacy, as well as external factors: preparedness and having skills for intervention during emergencies along with gender best, predict potential helping behaviors. These results broaden our view of bystander behavior and open a window for enhancing this phenomenon as another element in disaster and crisis management.

Keywords: bystander behavior, disasters emergencies, psychological motivation to help, social context for helping

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3334 Up-Scaling of Highly Transparent Quasi-Solid State Dye-Sensitized Solar Devices Composed of Nanocomposite Materials

Authors: Dimitra Sygkridou, Andreas Rapsomanikis, Elias Stathatos, Polycarpos Falaras, Evangelos Vitoratos

Abstract:

At the present work highly transparent strip type quasi-solid state dye-sensitized solar cells (DSSCs) were fabricated through inkjet printing using nanocomposite TiO2 inks as raw materials and tested under outdoor illumination conditions. The cells, which can be considered as the structural units of large area modules, were fully characterized electrically and electrochemically and after the evaluation of the received results a large area DSSC module was manufactured. The module design was a sandwich Z-interconnection where the working electrode is deposited on one conductive glass and the counter electrode on a second glass. Silver current collective fingers were printed on the conductive glasses to make the internal electrical connections and the adjacent cells were connected in series and finally insulated using a UV curing resin to protect them from the corrosive (I-/I3-) redox couple of the electrolyte. Finally, outdoor tests were carried out to the fabricated dye-sensitized solar module and its performance data were collected and assessed.

Keywords: dye-sensitized solar devices, inkjet printing, quasi-solid state electrolyte, transparency, up-scaling

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3333 Robust Recognition of Locomotion Patterns via Data-Driven Machine Learning in the Cloud Environment

Authors: Shinoy Vengaramkode Bhaskaran, Kaushik Sathupadi, Sandesh Achar

Abstract:

Human locomotion recognition is important in a variety of sectors, such as robotics, security, healthcare, fitness tracking and cloud computing. With the increasing pervasiveness of peripheral devices, particularly Inertial Measurement Units (IMUs) sensors, researchers have attempted to exploit these advancements in order to precisely and efficiently identify and categorize human activities. This research paper introduces a state-of-the-art methodology for the recognition of human locomotion patterns in a cloud environment. The methodology is based on a publicly available benchmark dataset. The investigation implements a denoising and windowing strategy to deal with the unprocessed data. Next, feature extraction is adopted to abstract the main cues from the data. The SelectKBest strategy is used to abstract optimal features from the data. Furthermore, state-of-the-art ML classifiers are used to evaluate the performance of the system, including logistic regression, random forest, gradient boosting and SVM have been investigated to accomplish precise locomotion classification. Finally, a detailed comparative analysis of results is presented to reveal the performance of recognition models.

Keywords: artificial intelligence, cloud computing, IoT, human locomotion, gradient boosting, random forest, neural networks, body-worn sensors

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3332 Automatic Identification of Pectoral Muscle

Authors: Ana L. M. Pavan, Guilherme Giacomini, Allan F. F. Alves, Marcela De Oliveira, Fernando A. B. Neto, Maria E. D. Rosa, Andre P. Trindade, Diana R. De Pina

Abstract:

Mammography is a worldwide image modality used to diagnose breast cancer, even in asymptomatic women. Due to its large availability, mammograms can be used to measure breast density and to predict cancer development. Women with increased mammographic density have a four- to sixfold increase in their risk of developing breast cancer. Therefore, studies have been made to accurately quantify mammographic breast density. In clinical routine, radiologists perform image evaluations through BIRADS (Breast Imaging Reporting and Data System) assessment. However, this method has inter and intraindividual variability. An automatic objective method to measure breast density could relieve radiologist’s workload by providing a first aid opinion. However, pectoral muscle is a high density tissue, with similar characteristics of fibroglandular tissues. It is consequently hard to automatically quantify mammographic breast density. Therefore, a pre-processing is needed to segment the pectoral muscle which may erroneously be quantified as fibroglandular tissue. The aim of this work was to develop an automatic algorithm to segment and extract pectoral muscle in digital mammograms. The database consisted of thirty medio-lateral oblique incidence digital mammography from São Paulo Medical School. This study was developed with ethical approval from the authors’ institutions and national review panels under protocol number 3720-2010. An algorithm was developed, in Matlab® platform, for the pre-processing of images. The algorithm uses image processing tools to automatically segment and extract the pectoral muscle of mammograms. Firstly, it was applied thresholding technique to remove non-biological information from image. Then, the Hough transform is applied, to find the limit of the pectoral muscle, followed by active contour method. Seed of active contour is applied in the limit of pectoral muscle found by Hough transform. An experienced radiologist also manually performed the pectoral muscle segmentation. Both methods, manual and automatic, were compared using the Jaccard index and Bland-Altman statistics. The comparison between manual and the developed automatic method presented a Jaccard similarity coefficient greater than 90% for all analyzed images, showing the efficiency and accuracy of segmentation of the proposed method. The Bland-Altman statistics compared both methods in relation to area (mm²) of segmented pectoral muscle. The statistic showed data within the 95% confidence interval, enhancing the accuracy of segmentation compared to the manual method. Thus, the method proved to be accurate and robust, segmenting rapidly and freely from intra and inter-observer variability. It is concluded that the proposed method may be used reliably to segment pectoral muscle in digital mammography in clinical routine. The segmentation of the pectoral muscle is very important for further quantifications of fibroglandular tissue volume present in the breast.

Keywords: active contour, fibroglandular tissue, hough transform, pectoral muscle

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